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The Power of Microarray Technology. Ruth G. Alscher. Gene Expression: Control Points. Responses to Environmental Signals. Glycolysis, Citric Acid Cycle, and Related Metabolic Processes. Free Radicals Attack Cells: Survival Mechanisms? . ROS Arise as a Result of Exposure to:. Ozone

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slide6

ROS Ariseas a Result of Exposure to:

  • Ozone
  • Sulfur dioxide
  • High light
  • Paraquat
  • Extremes of temperature
  • Salinity
  • Drought
effects of drought stress on gene expression in loblolly pine trees
Effects of Drought Stress on Gene Expression in Loblolly Pine Trees

-

Virginia Tech: determining which genes are essential for resistance to stress

Plant Biologists: Drs. Alscher and Chevone., Cecilia Vasquez

CS: Drs. Heath and Ramakrishnan, Margaret Ellis, Logan Hanks

Statistics: Dr Key, Xiao Yang.

NC State(Forest Biotechnology): discovering new genes in loblolly pine.

Ying-Hsuan Sun, Drs. Sederoff and Whetten:

slide9

Investigating gene expression patterns in stressed loblolly pine

Selected cDNAs are spotted on to a glass surface (can be up to 20,000 different sequences spotted on to one slide).

cDNAs derived from mRNA populations obtained from treated or control tree are hybridized to the cDNAs on the slide.

slide11

RelativeAbundance

Detection

Detection

Treatment

Control

1

2

1

2

1

2

2

3

1

3

3

3

Emission

Excitation

Mix

1

2

3

1

2

3

Spots:

(Sequences affixed to slide)

Hybridization

slide13

Iterative strategy for detection of genetic interactions using microarrays

Detection of gene expression effects on microarrays

1

Genetic Regulatory Networks

Test mutant phenotypes

Characterize gene function

4

2

3

Identify mutants

slide14

Design of Microarrays

  • Clones on the drought-stress microarrays werereplicated and randomly placed
  • Experiment involved 384 archived pine ESTs
  • Organized into 4 microtitre source plates after PCR
  • Pipetted into 8 sets of 4 microtitre plates each
  • Each set a different random arrangement of 384 ESTs
  • Printed type A microarrays from first 4 sets
  • Printed type B microarrays from second 4 sets
  • Each array has 4 randomly placed replicates of each EST
  • Each control versus stress comparison was done on 4 arrays — A and B; flip dyes; A and B
  • Total of 16 replicates of each EST in each comparison
slide15

Who’s Who

Computer Science

Plant Biology

Virginia Tech

Ruth Alscher

Plant Stress

Lenwood Heath (CS)

Algorithms

Virginia Tech

Dawei Chen

Molecular Biology

Bioinformatics

Boris Chevone

Plant Stress

Naren Ramakrishnan (CS)

Data Mining

Problem Solving Environments

Ron Sederoff,

Ross Whetten

Len van Zyl

Y-H.Sun

Forest Biotechnology

North Carolina State Univ.

Craig Struble,

Vincent Jouenne (CS)

Image Analysis

Ina Hoeschele (DS)

Statistical Genetics

Keying Ye (STAT)

Bayesian Statistics

Statistics

Virginia Tech

slide16

Expresso People

Ron Sederoff

Craig Struble

Lenny Heath

Ruth Alscher

Keying Ye

Ross Whetten

Vincent Jouenne

Boris Chevone

Len van Zyl

Y-H .Sun

Dawei Chen

Naren Ramakrishnan

slide17

Hypotheses

  • There is a group of genes whose expression confers resistance to drought stress.
  • Expression of this group of genes is lower under severe than under mild stress.
  • Individual members of gene families show distinct responses to drought stress.
slide18

Selection of cDNAs for Arrays

  • 384 ESTs (xylem, shoot tip cDNAs of loblolly) were chosen on the basis of function and grouped into categories.
  • Major emphasis was on processes known to be stress responsive.
  • In cases where more than one EST had similar BLAST hits, all ESTs were used.
slide19

Expresso: A Problem Solving Environment for Microarray Experiment Design and Analysis

  • Integration of design and procedures
  • Integration of image analysis tools and statistical analysis
  • Connections to web databases and sequence alignment tools
  • The software Aleph was used for inductive logic programming (ILP).
slide20

Categories within Protective and Protected Processes

Gene

Expression

Signal

Transduction

Protease-associated

ROS and Stress

Nucleus

Environmental

Change

Protective

Processes

Cell Wall Related

Trafficking

Phenylpropanoid

Pathway

Secretion

Cells

Cytoskeleton

Development

Tissues

Plant Growth Regulation

Protected

Processes

Chloroplast Associated

Metabolism

Carbon Metabolism

Respiration and Nucleic Acids

Mitochondrion

slide21

A Note about Categories

  • Categories are not mutually exclusive; gene(s) may be assigned to more then one category. For example, heat shock proteins have been grouped under these different categories and subcategories
    • Abiotic stress – heat
    • Gene expression – post-translational processing – chaperones
    • Abiotic stress - chaperones
slide22

Drought

Dehydrins, Aquaporins

Heat

Heat shock proteins

(Chaperones)

Abiotic

Non-Plant

Biotic

Cytosolic

ascorbate

peroxidase

Xenobiotics

GSTs

“Isoflavone

Reductases”

Chaperones

Antioxidant

Processes

superoxide

dismutase-Fe

NADPH/Ascorbate/

Glutathione

Scavenging Pathway

superoxide

dismutase-Cu-Zn

Sucrose Metabolism

Stress

glutathione

reductase

Cellulose

Protective

Processes

Cell Wall Related

Arabionogalactan proteins

Extensins and proline rich proteins

Phenylpropanoid

Pathway

Hemicellulose

Pectins

Xylose

4-coumarate-CoA

ligases

Other Cell Wall Proteins

Lignin Biosynthesis

CCoAOMTs

isoflavone reductases

cinnamyl-alcohol

dehydrogenase

phenylalanine ammonia-lyases

S-adenosylmethionine decarboxylases

glycine hydromethyltransferases

Categories

within

“Protective

Processes”

slide23

Quality Control

  • Positive: LP-3, a loblolly gene known to respond positively to drought stress in loblloly pine, was included.
  • LP-3 was positive in the moist versus mild comparison, and unchanged in the moist versus severe comparison.
  • Negative: Four clones of human genes used as negative controls in the Arabidopsis Functional Genomics project were included. The clones did not respond.
slide24

Spot and Clone Analysis

  • Image Analysis: gridding, spot identification, intensity and background calculation, normalization
  • Statistics:
    • Fold or ratio estimation
    • Combining replicates
  • Higher-level Analysis:
    • Clustering methods
    • Inductive logic programming (ILP)
slide25

Current Status of Expresso

  • Completely automated and integrated
    • Statistical analysis
    • Data mining
    • Experiment capture in MEL
  • Current Work: Integrating
    • Image processing
    • Querying by semi-structured views
    • Expresso-assisted experiment composition
slide26

Future Directions

Next Generation Stress Chips

  • Time course, short and long term, to capture gene expression events underlying “emergency” and adaptive events following drought stress imposition.
  • (Use all available ESTs for candidate stress resistance genes.)
  • Generate cDNA library from stressed seedlings.
  • Initiate modeling of kinetics of drought stress responses.
slide27

Microarray Data Analysis

How to use microarrays to learn more about the influence of drought stress on gene expression?

Where the biologists need the computer scientists.

A. Confounding factors in the raw data

1. Limitations in accuracy (technique)

2. Biological variation (individuals)

B. How to apply corrections for these confounding factors to maximize the predictive power of the data.

C. Modeling regulatory networks.